Liver-Specific Polygenic Risk Score Is Associated with Alzheimer’s Disease Diagnosis

Article type: Research Article

Authors: Panyard, Daniel J.^{a; 1} | Deming, Yuetiva K.^{a; b; c} | Darst, Burcu F.^d | Van Hulle, Carol A.^{b; c} | Zetterberg, Henrik^{e; f; g; h; i} | Blennow, Kaj^{e; f} | Kollmorgen, Gwendlyn^j | Suridjan, Ivonne^k | Carlsson, Cynthia M.^{b; c; l; m} | Johnson, Sterling C.^{b; c; l; m} | Asthana, Sanjay^{b; c; m} | Engelman, Corinne D.^{a; 2} | Lu, Qiongshi^{n; o; *; 2}

Affiliations: [a] Department of Population Health Sciences, University of Wisconsin-Madison, Madison, WI, USA | [b] Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin-Madison, Madison, WI, USA | [c] Department of Medicine, University of Wisconsin-Madison, Madison, WI, USA | [d] Center for Genetic Epidemiology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA | [e] Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden | [f] Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden | [g] Department of Neurodegenerative Disease, UCL Institute of Neurology, London, UK | [h] UK Dementia Research Institute at UCL, London, UK | [i] Hong Kong Center for Neurodegenerative Diseases, Hong Kong, China | [j] Roche Diagnostics GmbH, Penzberg, Germany | [k] Roche Diagnostics International Ltd., Rotkreuz, Switzerland | [l] Wisconsin Alzheimer’s Institute, University of Wisconsin-Madison, Madison, WI, USA | [m] William S. Middleton Memorial Veterans Hospital, Madison, WI, USA | [n] Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, WI, USA | [o] Department of Statistics, University of Wisconsin-Madison, Madison, WI, USA

Correspondence: [*] Correspondence to: Qiongshi Lu, University of Wisconsin-Madison, #2104, Biotechnology Center, 425 Henry Mall, Madison, WI 53706, USA. Tel.: +1 6082622392; E-mail: qlu@biostat.wisc.edu.

Note: [1] Current address: Department of Genetics, School of Medicine, Stanford University, Stanford, CA, USA.

Note: [2] Denotes joint senior authorship.

Abstract: Background:Our understanding of the pathophysiology underlying Alzheimer’s disease (AD) has benefited from genomic analyses, including those that leverage polygenic risk score (PRS) models of disease. The use of functional annotation has been able to improve the power of genomic models. Objective:We sought to leverage genomic functional annotations to build tissue-specific AD PRS models and study their relationship with AD and its biomarkers. Methods:We built 13 tissue-specific AD PRS and studied the scores’ relationships with AD diagnosis, cerebrospinal fluid (CSF) amyloid, CSF tau, and other CSF biomarkers in two longitudinal cohort studies of AD. Results:The AD PRS model that was most predictive of AD diagnosis (even without APOE) was the liver AD PRS: n = 1,115; odds ratio = 2.15 (1.67–2.78), p = 3.62×10–9. The liver AD PRS was also statistically significantly associated with cerebrospinal fluid biomarker evidence of amyloid-β (Aβ42:Aβ40 ratio, p = 3.53×10–6) and the phosphorylated tau:amyloid-β ratio (p = 1.45×10–5). Conclusion:These findings provide further evidence of the role of the liver-functional genome in AD and the benefits of incorporating functional annotation into genomic research.

Keywords: Alzheimer’s disease, cerebrospinal fluid biomarkers, functional annotation, liver, polygenic risk score

DOI: 10.3233/JAD-220599

Journal: Journal of Alzheimer's Disease, vol. 92, no. 2, pp. 395-409, 2023